Nick Terrel

Nick is the Data Administrator at CAIDA, where he works on the systems that collect, process, preserve, and distribute Internet measurement data. He holds a PhD in Physical Chemistry, with a background in machine learning, GPU-accelerated computing, and large-scale scientific data analysis.

Contact Information

Nick Terrel

From active learning to active measurement

Nick earned his PhD in Physical Chemistry in 2025 from the University of Florida, focusing on large-scale data and systems work: machine-learned interatomic potential models and large-scale molecular dynamics simulations distributed across thousands of GPUs. This work produced on the order of 100 TB of raw simulation data that had to be stored, validated, and analyzed reproducibly in scalable data pipelines. Building those pipelines, as well as the GPU-accelerated workflows that capable of extracting millions of novel molecules from this messy data

The same problems define CAIDA’s work: large distributed datasets, reproducible pipelines, provenance and validation, and long-lived research infrastructure that has to keep running while it is modernized. As Data Administrator, Nick brings that systems-oriented approach to how CAIDA collects, curates, and distributes Internet measurement data — including the careful, incremental modernization of mature Perl and Unix workflows into maintainable Python.

Interests

Internet measurement data infrastructure and research dataset stewardship
Scientific software engineering and reproducible data pipelines
Legacy-system modernization; distributed, high-performance data processing